Accelerating the Development of Liquid Electrolytes for Lithium Batteries with Self-Driving Labs

The development of functional electrolytes for lithium batteries requires the optimization of various combinations of salts, solvents, and additives, a process that is traditionally time- and resource-intensive. To accelerate this, computational methods are employed to pre-select candidate combinations, and efforts are underway to utilize self-driving labs (SDLs) powered by AI and robotic automation to efficiently explore optimal electrolyte formulations. By automating electrolyte preparation, battery assembly, and electrochemical analysis, SDLs can rapidly identify optimal combinations with fewer experiments. In this talk, I will introduce the A utomated L i-ion BA ttery T esting RO bot S ystem (ALBATROSS), which allows us to explore new electrolytes by autonomously formulating combinations of salts, solvents, and additives, assembling coin cells, and testing their performance using battery cycling and electrochemical impedance spectroscopy (EIS), all without human intervention. I will also discuss the challenges that must be addressed for the practical implementation of SDLs in the development of battery materials.